Olatunji Johnson

Olatunji Johnson

Dr

  • Department of Mathematics, The University of Manchester, Alan Turing Building, Oxford Road

    M13 9PL Manchester

    United Kingdom

Accepting PhD Students

Personal profile

Overview

Dr Olatunji Johnson is a lecturer in statistics in the department of mathematics. He did his PhD in Statistics and Epidemiology where he developed geostatistical methods for analysing spatially aggregated data. His PhD was under the supervision of Prof. Peter Diggle, Dr Emanuele Giorgi and Prof Jo Knight. He is the author of the SDALGCP and MBGapp R package. He has used Model-based Geostatistical (MBG) methods to provide valuable answers to many global public health questions and support informed decision-making in low-resource settings.  He has worked and currently working on several global public health problems including COPD, malaria and neglected tropical diseases (NTDs) such as river blindness, soil-transmitted helminths, schistosomiasis, Trachoma, Loiasis.

I am actively looking for PhD students interested in working on spatial and spatio-temporal statistics with applications in global public health. Please get in touch if you are interested in this area.

Research interests

My research interests lie in the interface of statistics, epidemiology and health informatics with a particular interest in spatial statistics, public health and environmental epidemiology. I am interested in developing novel model-based geostatistical methods for tropical disease mapping.

My methodological themes include spatial and spatio-temporal statistics; joint modelling of multiple outcomes; geostatistical methods for spatial misalignment.

My application themes include real-time health surveillance; tropical disease mapping; environmental epidemiology.

I am looking for PhD students to work on the following topics:

1. Modelling clustering geo-referenced data via mixtures.

2. Inference for multivariate spatio-temporal models.

3. Hybrid geostatistical and machine learning approaches for analysing spatial data.

4. Modelling spatially misaligned data.

 

 

 

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Research Beacons, Institutes and Platforms

  • Digital Futures
  • Christabel Pankhurst Institute

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Collaborations and top research areas from the last five years

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